AIMC Topic: Observer Variation

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Spine surgeon versus AI algorithm full-length radiographic measurements: a validation study of complex adult spinal deformity patients.

Spine deformity Feb 9, 2024
INTRODUCTION: Spinal measurements play an integral role in surgical planning for a variety of spine procedures. Full-length imaging eliminates distortions that can occur with stitched images. However, these images take radiologists significantly long...
Artificial Intelligence Algorithms Female Reproducibility of Results Humans Spine Observer Variation Lordosis Spinal Curvatures Adult Male Middle Aged Radiography
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Deep-Learning Reconstruction of High-Resolution CT Improves Interobserver Agreement for the Evaluation of Pulmonary Fibrosis.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes Jan 31, 2024
This study aimed to investigate whether deep-learning reconstruction (DLR) improves interobserver agreement in the evaluation of honeycombing for patients with interstitial lung disease (ILD) who underwent high-resolution computed tomography (CT) co...
Humans Aged Aged, 80 and over Male Middle Aged Retrospective Studies Tomography, X-Ray Computed Female Reproducibility of Results Lung Diseases, Interstitial Observer Variation Lung Deep Learning Radiographic Image Interpretation, Computer-Assisted Pulmonary Fibrosis
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Reader bias in breast cancer screening related to cancer prevalence and artificial intelligence decision support-a reader study.

European radiology Jan 2, 2024
OBJECTIVES: The aim of our study was to examine how breast radiologists would be affected by high cancer prevalence and the use of artificial intelligence (AI) for decision support.
Early Detection of Cancer Mammography Observer Variation Female Aged Adult Sensitivity and Specificity Breast Neoplasms Middle Aged Prevalence Humans Decision Support Systems, Clinical Artificial Intelligence
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MRI Deep Learning-Based Automatic Segmentation of Interventricular Septum for Black-Blood Myocardial T2* Measurement in Thalassemia.

Journal of magnetic resonance imaging : JMRI Nov 9, 2023
BACKGROUND: The T2* value of interventricular septum is routinely reported for grading myocardial iron load in thalassemia major, and automatic segmentation of septum could shorten analysis time and reduce interobserver variability.
Iron Overload Thalassemia Observer Variation Ventricular Septum Image Processing, Computer-Assisted Magnetic Resonance Imaging Myocardium beta-Thalassemia Female Reproducibility of Results Young Adult Adult Male Middle Aged Humans Deep Learning Adolescent Retrospective Studies
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Improving mammography interpretation for both novice and experienced readers: a comparative study of two commercial artificial intelligence software.

European radiology Nov 8, 2023
OBJECTIVES: To evaluate the improvement of mammography interpretation for novice and experienced radiologists assisted by two commercial AI software.
Radiologists Radiographic Image Interpretation, Computer-Assisted Observer Variation Breast Neoplasms Middle Aged Clinical Competence Mammography Humans Artificial Intelligence Software Female Reproducibility of Results Aged Adult Sensitivity and Specificity
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Deep learning assisted measurement of echocardiographic left heart parameters: improvement in interobserver variability and workflow efficiency.

The international journal of cardiovascular imaging Oct 23, 2023
Machine learning techniques designed to recognize views and perform measurements are increasingly used to address the need for automation of the interpretation of echocardiographic images. The current study was designed to determine whether a recentl...
Humans Observer Variation Reproducibility of Results Deep Learning Echocardiography, Three-Dimensional Predictive Value of Tests Echocardiography Workflow Heart Ventricles
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Automated Breast Density Assessment in MRI Using Deep Learning and Radiomics: Strategies for Reducing Inter-Observer Variability.

Journal of magnetic resonance imaging : JMRI Oct 17, 2023
BACKGROUND: Accurate breast density evaluation allows for more precise risk estimation but suffers from high inter-observer variability.
Observer Variation Aged Breast Density Adult Humans Breast Neoplasms Magnetic Resonance Imaging Middle Aged Retrospective Studies Radiomics Deep Learning Female Breast ROC Curve Reproducibility of Results Feasibility Studies Image Processing, Computer-Assisted Image Interpretation, Computer-Assisted
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Editorial for "Automated Breast Density Assessment in MRI Using Deep Learning and Radiomics: Strategies for Reducing Inter-Observer Variability".

Journal of magnetic resonance imaging : JMRI Oct 11, 2023
Image Processing, Computer-Assisted Magnetic Resonance Imaging Reproducibility of Results Breast Breast Neoplasms Observer Variation Breast Density Humans Radiomics Female Deep Learning
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Reference standard for the evaluation of automatic segmentation algorithms: Quantification of inter observer variability of manual delineation of prostate contour on MRI.

Diagnostic and interventional imaging Aug 21, 2023
PURPOSE: The purpose of this study was to investigate the relationship between inter-reader variability in manual prostate contour segmentation on magnetic resonance imaging (MRI) examinations and determine the optimal number of readers required to e...
Humans Artificial Intelligence Algorithms Male Magnetic Resonance Imaging Prostate Observer Variation
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Accelerated Measurement of Carotid Plaque Volume Using Artificial Intelligence Enhanced 3D Ultrasound.

Annals of vascular surgery Jun 22, 2023
BACKGROUND: Carotid plaque volume (CPV) can be measured by 3D ultrasound and may be a better predictor of stroke than stenosis, but analysis time limits clinical utility. This study tested the accuracy, reproducibility, and time saved of using an art...
Imaging, Three-Dimensional Plaque, Atherosclerotic Humans Treatment Outcome Artificial Intelligence Observer Variation Reproducibility of Results Carotid Arteries Ultrasonography
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